Gene polymorphisms of inflammatory factors in liver cirrhosis
Bibliographic record
Abstract
Introduction: Studies on the association between gene polymorphisms of various inflammatory factors and liver cirrhosis have been inconsistent. The purpose of this study was to comprehensively summarize the available evidence on the association between gene polymorphisms of inflammatory factors and liver cirrhosis through a systematic review. Methods: We searched databases of PubMed, EMBASE, Web of Science, and the Cochrane Library for relevant articles published from building databases to 25 September 2022. A systematic review and meta‐analysis were performed to investigate the association between gene polymorphisms of various inflammatory factors and liver cirrhosis. Odds ratios (OR) and 95% confidence intervals (CI) were used to assess the strength of association. Results: A total of 43 articles were included in the systematic review and of them, 22 articles were included in the meta‐analysis. The gene polymorphisms of IL-10–1082 GA + AA vs. GG (OR = 1.43, 95% CI = 1.12–1.83), IL-10–1082 AA vs. GG (OR = 2.03, 95% CI = 1.36–3.02), IL-18 -137 GG vs. CC (OR = 3.84, 95% CI = 1.29–11.40), TGF-β1 -509 T vs. C (OR = 2.52, 95% CI = 1.42–4.48), and IFN-γ +874 T vs. A (OR = 1.98, 95% CI = 1.32–2.98) were associated with liver cirrhosis significantly and no association was observed in other gene polymorphisms included in the meta‐analysis. The review of inflammatory factors gene polymorphisms that were only reported by a single study indicated 19 gene polymorphisms were risk factors and 4 gene polymorphisms were protective factors for liver cirrhosis, while the association between other 27 gene polymorphisms and liver cirrhosis were not statistically significant. Discussion: This study suggests that IL-10 -1082G/A, IL-18 -137G/C, TGF-β1 -509T/C, and IFN-γ +874T/A were potentially associated with the risk of liver cirrhosis susceptibility. These findings may provide comprehensive evidence for genetic susceptibility and immunogenetic pathology of liver cirrhosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".